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| |computation_time_hardware=Desktop PC | | |computation_time_hardware=Desktop PC |
| |computation_time_comments=one year, one country | | |computation_time_comments=one year, one country |
| + | |citation_references=Nitsch, F., Schimeczek, C. (2021). "Back-testing the agent-based model AMIRIS for the Austrian day-ahead electricity market". Working Paper.Back-testing the agent-based model AMIRIS for the Austrian day-ahead electricity market |
| + | |citation_doi=https://elib.dlr.de/147128/1/Nitsch2021BacktestingAMIRIS.pdf |
| |Model input file format=No | | |Model input file format=No |
| |Model file format=No | | |Model file format=No |
| |Model output file format=No | | |Model output file format=No |
| }} | | }} |
Revision as of 16:38, 25 January 2022
Agent-based Market model for the Investigation of Renewable and Integrated energy Systems
by German Aerospace Center
Authors:
Contact: Christoph Schimeczek
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Agent-based electricty market model for analysing questions on future energy markets, their market design, and energy-related policy instruments
Based on Java. Using Python for data processing.
Website / Documentation
Download
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Open Source Apache License 2.0 (Apache-2.0)
Directly downloadable
Input data shipped
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Model Scope |
Model type and solution approach |
Model class
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Agent-based electricity market model
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Sectors
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electricity
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Technologies
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Renewables, Conventional Generation
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Decisions
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dispatch
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Regions
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Germany, Austria
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Geographic Resolution
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National
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Time resolution
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Hour
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Network coverage
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Model type
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Simulation, Agent-based
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algorithms for market clearing and agent-specific bidding strategies
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Variables
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Computation time
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1 minutes (one year, one country)
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Objective
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Uncertainty modeling
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stochastic, perfect foresight, deterministic
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Suited for many scenarios / monte-carlo
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Yes
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References
Scientific references
Nitsch, F., Schimeczek, C. (2021). "Back-testing the agent-based model AMIRIS for the Austrian day-ahead electricity market". Working Paper.Back-testing the agent-based model AMIRIS for the Austrian day-ahead electricity market
https://dx.doi.org/https://elib.dlr.de/147128/1/Nitsch2021BacktestingAMIRIS.pdf
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